"We are excited about Dr. Guerrero's innovator award," said Thomas Buchholz, M.D., professor and chair of the Department of Radiation Oncology. "His work represents a novel, noninvasive imaging method for better understanding of lung function, which will enable us to further personalize radiation treatment planning to provide the most effective and safe treatment of lung cancer."

Since 2003, Guerrero and colleagues have refined a mathematical program - an algorithm - designed to more accurately identify damaged areas of the lung. Their program applies a technology called deformable image registration (DIR) to CT scans to characterize breathing function in all areas of the lung.

"Our goal for lung cancer is to reduce toxicity caused when patients receive radiotherapy, and for COPD to characterize disease. Our research methods produce images of the distribution of lung function, or lack of lung function, throughout the lung in these patients," Guerrero said.

The NIH Innovator grant will fund a clinical trial that compares the use of Guerrero's program to target radiation at lung tumors with the current standard of image-guided targeting methods based on volume avoidance techniques. Loss of lung function will be compared between the two groups of patients.

"We're going to test the ability to reduce injury to the lung from radiation therapy for patients with advanced lung cancer," Guerrero said. "In the past we've irradiated through both good and bad parts of the lung to get to the tumor. Our algorithm will permit us to irradiate only through the nonfunctioning lung, which will allow us to preserve functioning areas and reduce overall injury to the lung."

A second study will tap CT images and clinical data from a national study called COPDgene to see whether the DIR algorithm will better characterize the damage done by a specific type of COPD.

There are two manifestations of COPD. Emphysema can be assessed with current imaging and analysis methods. "The other is small airway disease where a thickening of the walls in small airways causes air trapping. Lungs appear normal, but air is not ventilating regions beyond where airway narrowing occur. We expect to be able to identify the distribution of air trapping with this method."

The COPD research involves applying the algorithm to two separate CT images of a patient's lung, one captured when a patient holds a breath at inhalation and the other at exhalation. The program then couples information from the two images to create a detailed picture of lung function.

The lung cancer study applies the algorithm to four-dimensional CT imaging, which produces 10 images of a single breath.

"The ultimate goal is to develop software that can be incorporated into existing medical computer work stations for CT analysis and for radiation treatment planning in every hospital, large and small, in the country," Guerrero said.

Guerrero is the second NIH Innovator Award winner from MD Anderson. Gabor Balazsi, Ph.D., an assistant professor in MD Anderson's Department of Systems Biology, won one last year.

"NIH is pleased to be supporting early-stage investigators from across the country who are taking considered risks in a wide range of areas in order to accelerate research," said Francis S. Collins, M.D., Ph.D., director of the National Institutes of Health. "We look forward to the results of their work."

Guerrero has been at MD Anderson for 8 years. He earned his doctorate at UCLA under the direction of Edward J. Hoffman, Ph.D., co-inventor of Positron Emission Tomography. One of his graduate course projects led to the development of whole-body PET imaging.

He has been elected a top 10 researcher in cancer imaging twice by the readers of Medical Imaging magazine and holds an adjunct associate professorship in computational and applied mathematics at Rice University. 10/01/10